Virtualization of assets

ABSTRACT

Techniques for solving asset synthesis by integrating asset synthesis instances into a historical, virtual, or predicted workflow within an organization. The integration facilitates improving a parameter of the synthesis, such as cost or time. The result is a system that improves productivity in an organization and improves accuracy of workflow completion prediction within the organization.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to Indian Provisional PatentApplication No. 201941002991 filed Jan. 24, 2019 and Indian ProvisionalPatent Application No. 201941014155 filed Apr. 8, 2019, which are herebyincorporated by reference herein.

BACKGROUND

Today's modern business enterprises require and make use ofsophisticated information systems to acquire vital insights into theperformance or prospective future performance of their business relativeto goals, market metrics, competitive information, and the like. Thisclass of information products is known in the field today as ManagementInformation Systems (MIS) or Business Intelligence (BI) tools. Inaddition, businesses seek better ways to identify the right strategiesand new ideas that can help them grow, and information solutionssupporting these objectives are often referred to as CollaborationTechnologies, and Innovation Management Systems. Collectively theseinformation systems fall under the general category of Enterprise andMarketing Intelligence Systems and represent a critical part of today'sbusiness software and information systems marketplace.

A lot of assets are underutilized or improperly parameterized, resultingin a waste of resources, including both time and money. As such,organizations have hidden operating expenses in the form of waste. Whilemeeting enablers, meeting managers, and meeting schedulers are known tobring teams of humans together, a flaw with BI systems today is thatthey fail to properly parameterize assets for maximum utility. Althoughassets are interlinked in an organization, there are no tools toeffectively measure the impact of synthesizing the various assets.

SUMMARY

An effective strategy should parametrize assets to improve thepredictive and tracking power of allocating real world assets in avirtual synthesis. Such an approach can include measuring theeffectiveness of a synthesis instance, such as a meeting, that includeshuman and artificial assets by considering utilization cost, in bothtime and money, for the purpose of historical review and predictivepower. Techniques described in this paper address a number of painpoints related to meetings, such as lacking a proper agenda, no outcomedocuments, lack of planning in scheduling, proper stakeholderparticipation, no metrics to determine success, no clarity on assetutilization costs, no clarity on reflecting historical consensus, remoteparticipation or participation via a personal device. Other assets andinstances have other associated challenges to be overcome, and areaddressed in this paper.

A system utilizing the techniques described in this paper understandsand solves asset synthesis by integrating asset synthesis instances intoa historical, virtual, or predicted workflow within an organization. Theintegration facilitates improving a parameter of the synthesis, such ascost or time. The result is a system that improves productivity in anorganization and improves the accuracy of workflow completion predictionwithin the organization.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a diagram of an example of a system for performingasset-to-workflow synthesis.

FIG. 2 depicts a diagram of an example of a workflow generation engine.

FIG. 3 depicts a diagram of an example of a persona-to-personaconnectivity graph.

FIG. 4 depicts a diagram of an example of an asset synthesis engine.

FIG. 5 depicts a diagram of an example of a synchronized personainteraction outcome generation engine.

FIG. 6 depicts a diagram of an example of a workflow analytics engine.

FIG. 7 depicts a diagram of an example of a workflow-to-realityintegration engine.

FIG. 8 is a flowchart of an example of task completion.

FIG. 9 is a flowchart of an example of changing task priority.

FIGS. 10-42 are screenshots intended to illustrate an implementation.

DETAILED DESCRIPTION

FIG. 1 depicts a diagram 100 of an example of a system for performingasset-to-workflow synthesis. The diagram 100 includes acomputer-readable medium (CRM) 102, a business workflow datastore 104coupled to the CRM 102, a project workflow datastore 106 coupled to theCRM 102, a task workflow datastore 108 coupled to the CRM 102, anassignment workflow datastore 110 coupled to the CRM 102, a personadatastore 112 coupled to the CRM 102, a resource datastore 114 coupledto the CRM 102, a workflow generation engine 116 coupled to the CRM 102,a persona-to-persona connectivity engine 118 coupled to the CRM 102, asynchronized persona interaction (SPI) facilitation engine 120 coupledto the CRM 102, an asset synthesis instantiation engine 122 coupled tothe CRM 102, an SPI outcome generation engine 124 coupled to the CRM102, a workflow analytics engine 126 coupled to the CRM 102, andqualified resources 128 coupled to the CRM 102.

The CRM 102 and other computer readable mediums discussed in this paperare intended to include all mediums that are statutory (e.g., in theUnited States, under 35 U.S.C. 101), and to specifically exclude allmediums that are non-statutory in nature to the extent that theexclusion is necessary for a claim that includes the computer-readablemedium to be valid. Known statutory computer-readable mediums includehardware (e.g., registers, random access memory (RAM), non-volatile (NV)storage, to name a few), but may or may not be limited to hardware.

The CRM 102 and other computer readable mediums discussed in this paperare intended to represent a variety of potentially applicabletechnologies. For example, the CRM 102 can be used to form a network orpart of a network. Where two components are co-located on a device, theCRM 102 can include a bus or other data conduit or plane. Where a firstcomponent is co-located on one device and a second component is locatedon a different device, the CRM 102 can include a wireless or wiredback-end network or LAN. The CRM 102 can also encompass a relevantportion of a WAN or other network, if applicable.

The devices, systems, and computer-readable mediums described in thispaper can be implemented as a computer system or parts of a computersystem or a plurality of computer systems. In general, a computer systemwill include a processor, memory, non-volatile storage, and aninterface. A typical computer system will usually include at least aprocessor, memory, and a device (e.g., a bus) coupling the memory to theprocessor. The processor can be, for example, a general-purpose centralprocessing unit (CPU), such as a microprocessor, or a special-purposeprocessor, such as a microcontroller.

The memory can include, by way of example but not limitation, randomaccess memory (RAM), such as dynamic RAM (DRAM) and static RAM (SRAM).The memory can be local, remote, or distributed. The bus can also couplethe processor to non-volatile storage. The non-volatile storage is oftena magnetic floppy or hard disk, a magnetic-optical disk, an opticaldisk, a read-only memory (ROM), such as a CD-ROM, EPROM, or EEPROM, amagnetic or optical card, or another form of storage for large amountsof data. Some of this data is often written, by a direct memory accessprocess, into memory during execution of software on the computersystem. The non-volatile storage can be local, remote, or distributed.The non-volatile storage is optional because systems can be created withall applicable data available in memory.

Software is typically stored in the non-volatile storage. Indeed, forlarge programs, it may not even be possible to store the entire programin the memory. Nevertheless, it should be understood that for softwareto run, if necessary, it is moved to a computer-readable locationappropriate for processing, and for illustrative purposes, that locationis referred to as the memory in this paper. Even when software is movedto the memory for execution, the processor will typically make use ofhardware registers to store values associated with the software, andlocal cache that, ideally, serves to speed up execution. As used herein,a software program is assumed to be stored at an applicable known orconvenient location (from non-volatile storage to hardware registers)when the software program is referred to as “implemented in acomputer-readable storage medium.” A processor is considered to be“configured to execute a program” when at least one value associatedwith the program is stored in a register readable by the processor.

In one example of operation, a computer system can be controlled byoperating system software, which is a software program that includes afile management system, such as a disk operating system. One example ofoperating system software with associated file management systemsoftware is the family of operating systems known as Windows® fromMicrosoft Corporation of Redmond, Wash., and their associated filemanagement systems. Another example of operating system software withits associated file management system software is the Linux operatingsystem and its associated file management system. The file managementsystem is typically stored in the non-volatile storage and causes theprocessor to execute the various acts required by the operating systemto input and output data and to store data in the memory, includingstoring files on the non-volatile storage.

The bus can also couple the processor to the interface. The interfacecan include one or more input and/or output (I/O) devices. Dependingupon implementation-specific or other considerations, the I/O devicescan include, by way of example but not limitation, a keyboard, a mouseor other pointing device, disk drives, printers, a scanner, and otherI/O devices, including a display device. The display device can include,by way of example but not limitation, a cathode ray tube (CRT), liquidcrystal display (LCD), or some other applicable known or convenientdisplay device. The interface can include one or more of a modem ornetwork interface. It will be appreciated that a modem or networkinterface can be considered to be part of the computer system. Theinterface can include an analog modem, ISDN modem, cable modem, tokenring interface, satellite transmission interface (e.g. “direct PC”), orother interfaces for coupling a computer system to other computersystems. Interfaces enable computer systems and other devices to becoupled together in a network.

The computer systems can be compatible with or implemented as part of orthrough a cloud-based computing system. As used in this paper, acloud-based computing system is a system that provides virtualizedcomputing resources, software and/or information to end user devices.The computing resources, software and/or information can be virtualizedby maintaining centralized services and resources that the edge devicescan access over a communication interface, such as a network. “Cloud”may be a marketing term and for the purposes of this paper can includeany of the networks described herein. The cloud-based computing systemcan involve a subscription for services or use a utility pricing model.Users can access the protocols of the cloud-based computing systemthrough a web browser or other container application located on theirend user device.

A computer system can be implemented as an engine, as part of an engineor through multiple engines. As used in this paper, an engine includesone or more processors or a portion thereof. A portion of one or moreprocessors can include some portion of hardware less than all of thehardware comprising any given one or more processors, such as a subsetof registers, the portion of the processor dedicated to one or morethreads of a multi-threaded processor, a time slice during which theprocessor is wholly or partially dedicated to carrying out part of theengine's functionality, or the like. As such, a first engine and asecond engine can have one or more dedicated processors or a firstengine and a second engine can share one or more processors with oneanother or other engines. Depending upon implementation-specific orother considerations, an engine can be centralized or its functionalitydistributed. An engine can include hardware, firmware, or softwareembodied in a computer-readable medium for execution by the processor.The processor transforms data into new data using implemented datastructures and methods, such as is described with reference to thefigures in this paper.

The engines described in this paper, or the engines through which thesystems and devices described in this paper can be implemented, can becloud-based engines. As used in this paper, a cloud-based engine is anengine that can run applications and/or functionalities using acloud-based computing system. All or portions of the applications and/orfunctionalities can be distributed across multiple computing devices,and need not be restricted to only one computing device. In someembodiments, the cloud-based engines can execute functionalities and/ormodules that end users access through a web browser or containerapplication without having the functionalities and/or modules installedlocally on the end-users' computing devices.

As used in this paper, datastores are intended to include repositorieshaving any applicable organization of data, including tables,comma-separated values (CSV) files, traditional databases (e.g., SQL),or other applicable known or convenient organizational formats.Datastores can be implemented, for example, as software embodied in aphysical computer-readable medium on a specific-purpose machine, infirmware, in hardware, in a combination thereof, or in an applicableknown or convenient device or system. Datastore-associated components,such as database interfaces, can be considered “part of” a datastore,part of some other system component, or a combination thereof, thoughthe physical location and other characteristics of datastore-associatedcomponents is not critical for an understanding of the techniquesdescribed in this paper.

A database management system (DBMS) can be used to manage a datastore.In such a case, the DBMS may be thought of as part of the datastore, aspart of a server, and/or as a separate system. A DBMS is typicallyimplemented as an engine that controls organization, storage,management, and retrieval of data in a database. DBMSs frequentlyprovide the ability to query, backup and replicate, enforce rules,provide security, do computation, perform change and access logging, andautomate optimization. Examples of DBMSs include Alpha Five, DataEase,Oracle database, IBM DB2, Adaptive Server Enterprise, FileMaker,Firebird, Ingres, Informix, Mark Logic, Microsoft Access, InterSystemsCache, Microsoft SQL Server, Microsoft Visual FoxPro, MonetDB, MySQL,PostgreSQL, Progress, SQLite, Teradata, CSQL, OpenLink Virtuoso,Daffodil DB, and OpenOffice.org Base, to name several.

Database servers can store databases, as well as the DBMS and relatedengines. Any of the repositories described in this paper couldpresumably be implemented as database servers. It should be noted thatthere are two logical views of data in a database, the logical(external) view and the physical (internal) view. In this paper, thelogical view is generally assumed to be data found in a report, whilethe physical view is the data stored in a physical storage medium andavailable to a specifically programmed processor. With most DBMSimplementations, there is one physical view and an almost unlimitednumber of logical views for the same data.

A DBMS typically includes a modeling language, data structure, databasequery language, and transaction mechanism. The modeling language is usedto define the schema of each database in the DBMS, according to thedatabase model, which may include a hierarchical model, network model,relational model, object model, or some other applicable known orconvenient organization. An optimal structure may vary depending uponapplication requirements (e.g., speed, reliability, maintainability,scalability, and cost). One of the more common models in use today isthe ad hoc model embedded in SQL. Data structures can include fields,records, files, objects, and any other applicable known or convenientstructures for storing data. A database query language can enable usersto query databases, and can include report writers and securitymechanisms to prevent unauthorized access. A database transactionmechanism ideally ensures data integrity, even during concurrent useraccesses, with fault tolerance. DBMSs can also include a metadatarepository; metadata is data that describes other data.

As used in this paper, a data structure is associated with a particularway of storing and organizing data in a computer so that it can be usedefficiently within a given context. Data structures are generally basedon the ability of a computer to fetch and store data at any place in itsmemory, specified by an address, a bit string that can be itself storedin memory and manipulated by the program. Thus, some data structures arebased on computing the addresses of data items with arithmeticoperations; while other data structures are based on storing addressesof data items within the structure itself. Many data structures use bothprinciples, sometimes combined in non-trivial ways. The implementationof a data structure usually entails writing a set of procedures thatcreate and manipulate instances of that structure. The datastores,described in this paper, can be cloud-based datastores. A cloudbaseddatastore is a datastore that is compatible with cloud-based computingsystems and engines.

Business process management (BPM), as used in this paper, is a techniqueintended to align organizations with the needs of clients bycontinuously improving processes. BPM is an advantageous implementationbecause it tends to promote business efficacy while striving forinnovation and integration with technology. It should be noted thatbusiness process modeling and business process management are not thesame, and, confusingly, share the same acronym. In this paper, businessprocess management is given the acronym BPM, but business processmodeling is not given an acronym. Business process modeling is often,though not necessarily, used in BPM. Business process modeling is a wayof representing processes in systems or software. The models aretypically used as tools to improve process efficiency and quality, andcan use Business Process Modeling Notation (BPMN) or some other notationto model business processes.

A business process, as used in this paper, is a collection of relatedtasks that produce a service or product for a particular client.Business processes can be categorized as management processes,operational processes, and supporting processes. Management processesgovern the operation of a system, and include by way of example but notlimitation corporate governance, strategic management, etc. Operationalprocesses comprise the core business processes for a company, andinclude by way of example but not limitation, purchasing, manufacturing,marketing, and sales. Supporting processes support the core processesand include, by way of example but not limitation, accounting,recruiting, technical support, event organization, etc.

A business process can include multiple sub-processes, which have theirown attributes, but also contribute to achieving the goal of thesuper-process. For example, an operational process could include anevent organization task. (Event organization is sometimes referred to as“event management,” but “organization” is used here to avoid confusionwith a “management” sub-process.) The analysis of business processestypically includes the mapping of processes and sub-processes down toassignment level. A business process is sometimes intended to meanintegrating application software tasks, but this is narrower than thebroader meaning that is frequently ascribed to the term in the relevantart, and as intended in this paper. Although the initial focus of BPMmay have been on the automation of mechanistic business processes, ithas since been extended to integrate human-driven processes in whichhuman interaction takes place in series or parallel with the mechanisticprocesses.

Returning to the example of FIG. 1, the business workflow datastore 104is intended to represent data structure of an endeavor. In a specificimplementation, the endeavor includes assets associated with ownershipor board-level direction for a business, which in the aggregate definethe business workflow. While the titles associated with human agentsoperating at this level vary from company to company and country tocountry, they are referred to in this document as “directors,” with theunderstanding they could be referred to in some other manner (e.g.,chairman of the board, board member, investor, shareholder, owner,etc.). Directors sit at the top of a work hierarchy and have “business”as a work goal.

The business workflow datastore 104 and other datastores described inthis paper can have a corresponding engine to create, read, update, ordelete (CRUD) data structures. While not shown in FIG. 1, these enginesmay be described in association with other figures to illustraterelevant functionality.

The project workflow datastore 106 is intended to represent datastructures of projects. In a specific implementation, the projectsinclude assets associated with senior management, which in the aggregatedefine project workflows (of a business workflow). While the titlesassociated with human agents operating at this level vary from companyto company and country, they are referred to in this document as“officers,” with the understanding they could be referred to in someother manner (e.g., CEO or some other Chief-level officer, executivemanagement, upper management, president, vice president, generalmanager, etc.). Officers sit in the middle of a work hierarchy and have“projects” as a work goal. It is possible to have both a director and anofficer role in a company, but the director-level and officer-level workdone by such an individual can generally be distinguished by role withina workflow. A project can be subdivided into tasks, either explicitly atthe outset, or as need compels the creation of tasks to support aproject. Tasks are activities that are to be accomplished within adefined period of time or by a deadline; they are a small essentialpiece of a job that serves as a means to differentiate variouscomponents of a project. Tasks can be linked together to createdependencies. Task completion, particularly for linked tasks, benefitsfrom coordination, including integrating assets to meet a project goal.

The task workflow datastore 108 is intended to represent data structuresof tasks. In a specific implementation, the tasks include assetsassociated with middle management, which in the aggregate define taskworkflows (within project workflows). While the titles associated withhuman agents operating at this level vary from company to company andcountry, they are referred to in this document as “supervisors,” withthe understanding they could be referred to in some other manner (e.g.,vice president, general manager, manager, section head, team leader,foreman, etc.). Because officers and supervisors at different companiescan have the same title (e.g., vice president or general manager), adistinction by workflow and not by title is assumed in this document.Supervisors sit in the middle of a work hierarchy, below officers, andhave “tasks” as a work goal. It is possible to have both an officer role(or a director and officer role) and a supervisor role in a company, butthe officer-level (or director- and officer-level) and supervisor-levelwork done by such an individual can generally be distinguished by rolewithin a workflow. Projects and tasks have some similarities, and areoften associated with managers, but are broken into separate categoriesdue to both business procedures that recognize a distinction betweensenior management and middle management, as well as variations inworkflow that are worthy of distinction in this paper.

Task management has five or more conceptual breakdowns includingcreative (pertaining to task creation, such as planning, brainstorming,creation, elaboration, clarification, organization, reduction,targeting, and preliminary prioritization), functional (allowing forplanning, recurrence, dependency, reporting, tracking, prioritizing,configuring, delegating, testing, and managing of tasks), project(allowing for project task breakdown, task allocation, inventory acrossprojects, and concurrent access to task datastores), performance(allowing for tracking by time, cost control, stakeholder, priority, orthe like; charts, exportable reports, status updates, deadlineadjustments, and activity logging), and service (allowing for fileattachment and links to tasks, document management, access rightsmanagement, inventory of client and employee records, orders and callsmanagement, and annotating tasks) activities. Task status can includeready, terminated, expired, delegated, forwarded, finished, and failed;the workflow is generally from ready to terminated, expired, ordelegated and from delegated to ready (if the delegation is rejected),forwarded, finished, or failed. Task status may or may not also includeinactive and/or completed; the workflow can be from inactive to ready orcompleted and from terminated, expired, forwarded, finished, or failedto complete. (Other approaches, such as continuous delivery orcontinuous deployment, may call for alternative task statusdesignations.) Tasks are also differentiated by complexity, from low tohigh. A task can be broken down into assignments which typically have adefined start and end date or a deadline for completion. One or moreassignments on a task puts the task under execution. Completion of allassignments on a specific task normally renders the task completed(which can be characterized as an explicit status or as one of a groupof statuses, such as terminated, expired, forwarded, finished, andfailed). In most projects, tasks may suffer one of two major drawbacks:Task dependency and unclear understanding of the term complete. Anunderstanding of workflow dependencies, agents, and resources, alongwith tools to utilize and synchronize assets (as described withreference to FIG. 1) can ameliorate these drawbacks.

The assignment workflow datastore 110 is intended to represent datastructures of assignments. In a specific implementation, the assignmentdata structures include assets associated with staff, which in theaggregate define assignment workflows (within task workflows). Staff sitat the bottom of a work hierarchy and have “assignments” as a work goaland typically do not have a managerial title (though they may still havea title that carries some weight, such as senior engineer, or the like).It is possible to have both a staff-level and higher-level role in acompany, but the work done by such an individual can generally bedistinguished by role within a workflow. While assignment workflows aretreated as the most granular workflow in this paper, it may be notedassignments can be broken into sub-assignments, if applicable, allowingfor even finer resolution, but a detailed discussion is not deemednecessary in this paper because the techniques described herein arereadily applicable to sub-assignments.

The persona datastore 112 is intended to represent data structuresdefining human agents of an enterprise. In a specific implementation,persona data structures include the fields human resource cost,calendar, history, location, and scarcity. In an alternative, some“fields” may have time-varying values that are computed for a given dateand time and can be modified in response to dynamic workflow changes.For example, a human can only be in one location at a time, and locationmay be relevant now, historically (for prediction purposes), or at somefuture time (ideally as represented in the calendar). Scarcitydiminishes as the human associated with the persona is allocated toworkflows and increases when work is completed, and can be impacted bythe availability of assets that ameliorate location-based limitations(e.g., the ability to access relevant documents and conduct meetings viavideo conferencing technology from relatively remote locations) or theability to adjust responsibilities (e.g., by delaying one meeting infavor of another). Thus, for example, some portions of a persona datastructure may reside in a traditional database or non-volatile storageas part of a flat file, while other portions may be stored in RAM whilehuman agents associated with personas are considered for incorporationinto a workflow during workflow design.

The resource datastore 114 is intended to represent data structuresdefining non-human assets of an enterprise. “Of an enterprise” is notintended to mean all resources must be owned by an enterprise, just thatthey are available to the enterprise. For example, local catering, hotelaccommodations, available software licenses, and other resources can beconsidered a part of the resource datastore 114. Resources can includedevices, conference rooms, software, remote access, wireless LAN access,rental property, and other resources that can be used in a workflow.Different resources will have different parameters. For example,physical devices may include location (and/or capacity) and scarcityfields. The location can be an area for, e.g., wireless access pointsand may have an explicit capacity for, e.g., conference rooms. Softwarecan include a license field, which may include some restrictions on usethat are equivalent to “capacity” in some cases. The persona datastore112 and the resource datastore 114 can be referred to in the aggregateas an asset datastore.

The workflow generation engine 116 is intended to represent an enginethat populates workflow data structures with assets. In a specificimplementation, a human or artificial agent can change workflowparameters, such as asset availability, to predict when a workflow willbe completed, determine the impact of changing a workflow on otherworkflows, or the like. In a specific implementation, the workflowgeneration engine 116 provides a prediction regarding the probability aworkflow will go as planned. For example, if an asset is unreliable,reliance on the asset will result in an increased probability ofdisruption in the workflow. The workflow generation engine 116 canpopulate a workflow with asset synthesis instantiations using selectedworkflow parameters (and using, e.g., the asset synthesis instantiationengine 124).

The persona-to-persona connectivity engine 118 is intended to representan engine that synchronizes personas for interaction. Meeting enablersare available, such as Google Hangouts Meet, Skype for Business, and Goto Meeting, but such products only facilitate fixing a schedule for ameeting between humans, not personas representing agents of a workflow.By maintaining a virtual network of personas, rather than humans,personas can more readily be integrated into an asset synthesisinstantiation.

The SPI facilitation engine 120 is intended to represent an engine thatreduces real-world barriers to efficient incorporation of personas intoasset synthesis instantiations. Meeting schedulers are available, suchas Meetingbird, but such products fail to include workflow- andpersona-specific parameters in an automated workflow advancement engine(plus workflow-integrated recommendation engine for agents withdecision-making authority). By incorporating workflow parameters with avirtual network of personas, rather than humans with calendars, personascan more readily be integrated into an optimized workflow. (It may benoted that optimization can be for a variety of parameters, such ascost, completion time, throughput, etc.)

The asset synthesis instantiation engine 122 is intended to represent anengine that brings together virtual assets and personas in a manner thatoptimally utilizes the assets and personas for a configurable time spanin a configurable one or more locations as part of a workflow. Forsimplicity, it will generally be assumed “optimized” refers to a balanceof minimizing cost across workflows while meeting deadlines (usuallyimposed at a higher hierarchical level). Depending uponimplementation-specific, configuration-specific, or otherconsiderations, optimization can be for cost optimization for a span oftime, switched to speed optimization for some reason, such as when adeadline looms, or some other optimization, such as throughput, or ahybrid.

The SPI outcome generation engine 124 is intended to represent an enginethat facilitates workflow progress responsive to synchronized personainteraction. Meeting management products are available, such asMeetingsift and Meetingking, but such products only facilitate groupprocesses in in-room and remote meetings with task creations, notoutcome generation for synchronized personas. By using asset synthesisinstantiations that include personas and assets, rather than humanparticipants in meetings, characteristics of the various virtualcomponents, as well as results of any interaction, can more readily beintegrated into a workflow.

The workflow analytics engine 126 is intended to represent an enginethat analyzes the historical effectiveness of assets, including theeffectiveness of assets considered in the aggregate, e.g., for a givenworkflow or across workflows. Workflow analytics enables, e.g.,management to make qualitative (and quantitative) decisions regardingsuch things as compensation, maintenance schedules, trying alternativeproducts, or the like.

The qualified resources 128 are intended to represent network devices,end user devices, and other devices coupled to the computer-readablemedium 102, as well as conference rooms, furniture, and othercompositions of matter that are known to an enterprise. Qualified, asused here, is intended to mean detected via a network device, having atleast one characteristic detected via a sensor, available via a network,or explicitly qualified as an available resource by an agent. Thequalified resources 128 are represented in the resource datastore 114.The engines associated with generating new data for the datastores104-114 are considered part of the qualified resources 128. For example,a networked device may include a computer through which an administratorprovides values for parameters of a persona data structure in thepersona datastore 112, a camera and image analysis engine that creates apersona data structure for an unknown human detected by the camera (andperhaps later the data structure of the unknown human is merged withanother persona data structure if it turns out the unknown human and ahuman associated with an extant data structure are one in the same), oran RFID sensor for detecting an RFID tag affixed to an article ofclothing (data associated with the article of clothing can be stored inthe resource datastore 114 in association with the RFID tag in thisexample), to name a few. Thus, the qualified resources 128 haveassociated data structures in the resource datastore 114, but datastructures for people and objects that can be detected by at least onenetworked device (if not entered into the system in some other manner)are also “networked” in the sense they are known to the network, butwould not normally be considered “networked devices” per se. At leastsome of the qualified resources 128 could alternatively be referred toas things (as in “Internet of things”).

In a specific implementation, the resource datastore 114 can beaugmented dynamically when new physical resources are discovered, suchas in accordance with a bring your own device (BYOD) policy whenemployees bring their personal devices to work. In such animplementation, if the employee is represented in the persona datastore112, the persona data structure can be linked to the resource datastructure in the resource datastore 114 associated with the relevantpersonal device. In a specific implementation, the persona datastore 112can be augmented dynamically when a new person is discovered, such asvia security camera. In such an implementation, the resource used todetect the person can be linked to the persona data structure in thepersona datastore 112.

The workflow-to-reality integration engine 130 is intended to representan engine that integrates workflows with the real world. Advantageously,knowledge of workflow, persona, and resource data structures allows formeaningful historical analysis of real-world assets, rating or rewardingresources or personas, allocation of real-world assets to real-worldproblems, and prediction of real-world consequences for the allocationor for generating and completing workflows.

An example of operation, using FIG. 1 as an example, involves theworkflow generation engine 116 creating a business workflow datastructure in the business workflow datastore 104. The workflowgeneration engine 116 may receive input from a human agent representedwith a persona data structure in the persona datastore 112. The humanagent may utilize assets, such as a computer, office space, software,etc. with resource data structures in the resource datastore 114 tocreate the business workflow data structure. For conceptual purposes,the business workflow can be thought of as a framework onto whichprojects can be affixed. However, business workflows can be treated in amanner similar to projects (as described later), but for director-levelwork.

The persona-to-persona connectivity engine 118 facilitates connectingdirectors (or officers, supervisors, or staff) with one another oroutside personas. The persona-to-persona connectivity engine 118consults the persona datastore 112 to find potential connections (e.g.,via a contacts list) and potential connection timing (e.g., via acalendar). If a potential connection is not represented in the personadatastore 112, the persona data structure is created by providing atleast some information associated with the potential connection, whichwill typically include contact information. Depending uponimplementation-specific, preference, or other considerations, thepotential connection may be requested to RSVP if the persona-to-personaconnectivity engine 118 cannot authoritatively modify the potentialconnection's calendar (e.g., due to a lack of access to the relevantcalendar, permission, or the like).

The SPI facilitation engine 120 synchronizes personas virtually. Thesynchronization can be characterized as corresponding to, e.g., whatwould be referred to as a meeting in the physical world. The moreinformation available in the persona datastore 112, the greater thelikelihood of the virtual synchronization matching the actual meeting.For example, if the persona datastore 112 indicates a director will beavailable at the time of a potential meeting and that the director hasnothing else on his or her calendar, then the SPI facilitation engine120 can synchronize the persona of the director with other potentialattendees with a reasonable likelihood of the director being able toattend. Backups can be built in. For example, a director who is believedto be on location may turn out to be remote, but remote accesstechnology may be available to address the problem.

The asset synthesis instantiation engine 122 matches resources topersonas and integrates the synthesis into a workflow. Resources, suchas conference rooms or remote access technology, represented withresource data structures in the resource datastore 114, can be allocatedas applicable (if not already pre-allocated) to facilitate connectionsin the physical world. Asset synthesis instances are the footprint ofpast (historical), present (ongoing), or future (planned) events in thereal world that include at least one persona or resource at a set ofcoordinates in virtual space-time.

The SPI outcome generation engine 124 updates asset synthesis instanceswith data associated with the corresponding event in the real world.Advantageously, the SPI outcome generation engine 124 can updateworkflows in real time using sensors (such as cameras and microphones)or explicit input from humans at the event and, during or after theevent is over, generate reports regarding the event. Because theinstance is part of a workflow, outcomes become part of the workflow, aswell.

The workflow analytics engine 126 generates information about personasand resources useful to assess performance, predicts progress across oneor more workflows, and generates information useful in modeling futureworkflows.

The qualified resources 128 are used to instantiate the asset synthesisinstances in the real world. The qualified resources 128 act asfacilitators, such as a camera, network, and display used to establishlocal presence for a person when physical attendance is not possible; awireless access point (WAP) used to establish network connectivity forend-user devices; or a suitable conference room that acts as a locationin which attendees can gather, to name several.

The workflow-to-reality integration engine 130 provides an interface tohuman agents regarding the effectiveness of asset synthesis instances inthe real world.

FIG. 2 depicts a diagram 200 of an example of a workflow generationengine. The diagram 200 includes a project delegation engine 202, aprojects datastore 204 coupled to the project delegation engine 202, apersonas datastore 206 coupled to the project delegation engine 202, atask delegation engine 208 coupled to the project delegation engine 202and the personas datastore 206, a tasks datastore 210 coupled to thetask delegation engine 208, an assignment delegation engine 212 coupledto the task delegation engine 208 and the personas datastore 206, anassignments datastore 214 coupled to the assignment delegation engine212, and a resources datastore 216 coupled to the assignment delegationengine 212. The diagram 200 also includes a workflow prediction engine218 and an asset synthesis population engine 220 coupled to the abovecomponents.

The project delegation engine 202 is intended to represent an enginethat assigns projects in the projects datastore 204 to personas in thepersonas datastore 206. Assignment to a project can be by a human orartificial agent. In a specific implementation, newly created projectsinclude a set of tasks, each of which has task attributes, though theproject may initially not include all tasks and the tasks may or may notinclude all task attributes. Advantageously, as described below,personas can be updated over time based upon performance and the projectdelegation engine 202 can assign those personas that are most suited toa project based upon credentials and past performance.

The task delegation engine 208 is intended to represent an engine thatassigns tasks in the tasks datastore 210 to personas in the personasdatastore 206. Assignment to a task can be by a human or artificialagent. In a specific implementation, a task attribute change request fora new task that is added to an intentionally or unintentionallyincomplete project is approved by an officer and may trigger the taskdelegation engine 208 to assign a task to a new supervisor; officers mayor may not be responsible for approving some or all task attributechange requests, any of which can trigger the task delegation engine 208to re-assign a task. Advantageously, as described below, personas can beupdated over time based upon performance and the task delegation engine208 can assign those personas that are most suited to a task based uponcredentials and past performance.

The assignment delegation engine 212 is intended to represent an enginethat associates assignments in the assignments datastore 214 withpersonas in the personas datastore 206 and resources in the resourcesdatastore 216 to the assignment. Assignment can be by a human orartificial agent. Advantageously, as described below, personas can beupdated over time based upon performance and the assignment delegationengine 212 can assign those personas that are most suited to anassignment based upon credentials and past performance. Although theexample of FIG. 2 depicts the resources datastore 216 as coupled to theassignment delegation engine 212, depending uponimplementation-specific, preference-specific, or other considerations,resources could instead or in addition be assigned to tasks or projects.

The workflow prediction engine 218 is intended to represent an enginethat provides an interface to a human agent to facilitate workflowcompletion times, costs, odds of success, and/or other parameters. In aspecific implementation, the human agent can modify workflow parametersto obtain different predicted results for a particular allocation ofassets. In a specific implementation, the workflow prediction engine 218receives workflow analytics, described later, which improve predictionaccuracy.

The asset synthesis population engine 220 is intended to represent anengine that populates a workflow with placeholders for asset synthesisinstances generated by an asset synthesis instantiation engine. In aspecific implementation, the placeholder population is set by a human orartificial agent. In an alternative, the asset synthesis instantiationengine generates asset synthesis instances in lieu of placeholders,either at the time a workflow is generated or later.

An example of operation, using FIG. 2 as an example, involves theproject delegation engine 202 assigning to a project in the projectsdatastore 204 a persona in the persona datastore 206. In a specificimplementation, the projects are generated over the course of a businessworkflow by directors and the personas represent officers of a realworld enterprise.

The task delegation engine 208 assigns a task in the tasks datastore 210to a persona in the persona datastore 206. In a specific implementation,the tasks are generated over the course of a business workflow bydirectors as an explicit part of a project, by an officer assigned theproject, or in some other applicable manner, and the personas representsupervisors of a real world enterprise.

The assignment delegation engine 212 associates an assignment in theassignments datastore 214 to a persona in the persona datastore 206 andresources in the resources datastore 216. In a specific implementation,the assignments are generated over the course of a business workflow bydirectors as an explicit part of a project and a task of the project, byan officer as an explicit part of a project and a task of the project,by a supervisor as part of a task, or in some other applicable manner,and the personas represent staff of a real world enterprise.

The workflow prediction engine 218 provides predictions for selectedparameters as requested. The asset synthesis population engine 220inserts placeholders within a workflow for subsequent asset synthesisinstantiation.

FIG. 3 depicts a diagram 300 of an example of a persona-to-personaconnectivity graph. It may be noted the “n's” in the diagram 300 are notintended to represent the same number; two different n's may have twodifferent values. The diagram 300 includes a persona node 302 and apersona node 304-1 to a persona node 304-n (the persona nodes 304). Thepersona node 302 is coupled to the persona nodes 304 via a resource edge306-1 to a resource edge 306-n (the resource edges 306). The personanode 302 is coupled to the persona node 304-1 via a workflowrelationship edge 308. Each persona node 302, 304 can be coupled toother persona nodes via a workflow relationship edge (not shown), thoughthe workflow relationship edge can represent “no relationship.”

The persona node 302 is intended to represent an entry of a personadatastore that corresponds to a human agent. For illustrative purposes,it is assumed the human agent has a workflow assignment. The personanodes 304 are intended to represent other entries in the personadatastore that correspond to other humans.

The workflow resource edges 306 correspond to real-world resources thatare shared between the persona node 302 and the persona nodes 304. Theset of workflow resource edges between the persona node 302 and, e.g.,the persona node 304-1 can include a telephone number through which thehuman agent corresponding to the persona node 302 can contact the humanassociated with the persona node 304-1 (who may also have the telephonenumber of the human agent corresponding to the persona node 302), adial-in number and associated teleconference-supporting engines, anemail address, a shared drive, a conference room, a restaurantreservation, or some other device or location through which individualscan communicate either directly or indirectly that is known to anapplicable persona-to-persona connectivity engine.

The workflow relationship edge 308 corresponds to a workflow datastructure in a workflow datastore (e.g., a business, project, task, orassignment datastore). By maintaining a workflow relationship, an SPIfacilitation engine can more readily contribute to ease of managingworkflows. For example, by maintaining data on both connectivity, via aworkflow resource, and workflow relationship, it becomes significantlyeasier to evaluate work done by a human agent within the workflow andeffectiveness of a resource within the workflow, particularly asimpacted by an asset synthesis instance. In a specific implementation, ahuman agent can have an effectiveness rating associated with convertingbusiness development lunches into business (including time, cost,position, credentials, and other metrics), workflow advancement meetingswith other workflow stakeholders (including time and cost metrics, aswell as influence of respective stakeholders on the human agent),software utilization, or some other asset synthesis instance that linksa human agent with a resource or other human.

FIG. 4 depicts a diagram 400 of an example of an asset synthesis engine.The diagram 400 includes a task selection engine 402, a project workflowdatastore 404 coupled to the task selection engine 402, an agendacreation engine 406 coupled to the task selection engine 402, a taskworkflow datastore 408 coupled to the agenda creation engine 406, astakeholder invitation engine 410 coupled to the agenda creation engine406, a personas datastore 412 coupled to the stakeholder invitationengine 410, a resource allocation engine 414 coupled to the stakeholderinvitation engine 410, a resources datastore 416 coupled to the resourceallocation engine 414, an asset synthesis instance monitoring engine 418coupled to the resource allocation engine 414, and an assignmentworkflow datastore 420 coupled to the asset synthesis instancemonitoring engine 418.

The task selection engine 402 is intended to represent an engine thatselects a task from a project data structure in the project workflowdatastore 404. In a specific implementation, the task can be selected byeither a human agent or an artificial agent, depending upon the projectand/or task parameters. In this example, task selection is from aproject data structure, but other datastores (e.g., a task workflow,business workflow, assignment workflow, persona, or other datastore)could be used to assist in the selection. For example, if a personaparameter indicates a human agent corresponding to the persona datastructure functions better with more frequent supervision, tasks towhich the persona is assigned can be selected more frequently thantypical. As another example, if a resource parameter indicatesmaintenance of a resource should be scheduled with a certain frequency,tasks to which the resource is allocated can be selected in accordancewith the recommended schedule. As a third example, if a supervisor has apreference, tasks to which the supervisor is assigned can be scheduledin accordance with the supervisor's preference.

The agenda creation engine 406 is intended to represent an engine thatforms from a template an asset synthesis instance that includes anagenda designed to advance a task represented by a task workflow datastructure in the task workflow datastore 408. In a specificimplementation, asset synthesis instances build upon one another overtime. For example, the agenda creation engine 406 may have access tomeeting minutes, persona ratings, resource contribution ratings,transcripts, file histories, or the like of a first asset synthesisinstance for a task when creating an agenda for a second asset synthesisinstance for the task. In a meeting-specific example, there is a linkbetween previous meeting discussions (in form of minutes) on aparticular task. Hence the host can pick the agenda from previousdiscussion minutes on the same task. By utilizing meeting minutes orother relevant data, redundancy and other inefficiency can beameliorated in subsequent agendas. In a specific implementation, theagenda creation engine 406 can assign a sub-assignment (e.g.,responsibility for providing a status update in a meeting) to anappropriate persona so key personas are automatically populated for aselected agenda.

The stakeholder invitation engine 410 is intended to represent an enginethat contacts human agents represented by persona data structures in thepersonas datastore 412. Relevant personas are matched to the assetsynthesis instance by name, by role, or by some other parameter. In aspecific implementation, each relevant persona data structure includescontact information sufficient to invite respective human agents toparticipate in the asset synthesis instance. As teams grow, calendarsbecome so busy that manual scheduling becomes highly inefficient anddistracts from critical work. In a specific implementation, thestakeholder invitation engine 410 considers calendar settings ofpersonas and availability of resources to suggest a good time to meet.Depending upon implementation-specific, preference-specific, or otherconsiderations, supervisors can limit an asset synthesis instance to agiven time span (causing the stakeholder invitation engine 410 to settleon a time within the time span), require explicit RSVPs, make someparticipants optional, or constrain the stakeholder invitation engine410 in some other manner.

The resource allocation engine 414 is intended to represent an enginethat allocates qualified resources represented by resource datastructures in the resource datastore 416 to the asset synthesis instanceby identification, by type, or by some other parameter. In a specificimplementation, each relevant resource data structure includesidentifying information sufficient to inventory respective qualifiedresources used in the asset synthesis instance.

The asset synthesis instance monitoring engine 418 is intended torepresent an engine that monitors an asset synthesis instance in realtime. In a specific implementation, presence and participation areparameterized in an assignment workflow data structure in the assignmentworkflow datastore 420. The asset synthesis instance can be treated asan assignment with, if applicable, multiple associated personas. Thus,asset synthesis instances can be characterized as a type of assignmentwith a start time and an end time (plus, potentially start and end timesfor preparation and follow-up thereto). Due to the hierarchical natureof workflows, the assignment workflow data structure is part of theassignment workflow datastore 420, but also part of the task workflowdatastore 408 and the project workflow datastore 404. Also, theassignment workflow data structure includes a link (or reference) topersonas and resources in the personas datastore 412 and the resourcesdatastore 416, making aspects of the assignment workflow data structurepart of each.

As was previously mentioned, sub-assignments can be associated withpersonas of an asset synthesis instance, the resolution of which can beconverted into minutes, log files, or some other memorialization of thesub-assignment that can be made part of the assignment workflowdatastore 420. Sub-assignment resolutions can be shared with attendees,used to improve an agenda in the next meeting, used to rate a personaassigned to the sub-assignment, or the like.

FIG. 5 depicts a diagram 500 of an example of a synchronized personainteraction outcome generation engine. The diagram 500 includes aworkflow update engine 502, an assignment workflow datastore 504 coupledto the workflow update engine 502, a task attribute change requestresolution engine 506 coupled to the workflow update engine 502, a taskworkflow datastore 508 coupled to the task attribute change requestresolution engine 506, an asset synthesis instance cost computationengine 510 coupled to task attribute change request resolution engine506, a personas datastore 512 coupled to the asset synthesis instancecost computation engine 510, a resources datastore 514 coupled to theasset synthesis instance cost computation engine 510, and a projectworkflow datastore 516 coupled to the asset synthesis instance costcomputation engine 510.

The workflow update engine 502 is intended to represent an engine thatupdates an assignment data structure in the assignment workflowdatastore 504. In a specific implementation, the supervisor assigned toa task that includes the assignment workflow has the authority todelegate a persona to an assignment responsive to results of an assetsynthesis instance. The workflow update engine 502 can also create a newassignment data structure for a new assignment and delegate a persona toit, or delete an assignment data structure if the correspondingassignment is moot. A delegee will typically be given access to at leasta portion of the asset synthesis instance memorialization (e.g., meetingminutes).

The task attribute change request resolution engine 506 is intended torepresent an engine that generates a request to change task attributesbecause a supervisor is not authorized to make the change directly andupdates the task workflow datastore 508 if the request is approved. In aspecific implementation, the task attribute change request is providedto an officer for approval; if not approved, the task workflow datastore508 may or may not still be updated to keep a historical record of thedenied task attribute change request, which may be noteworthy inanalytics.

The asset synthesis instance cost computation engine 510 is intended torepresent an engine that computes multiple cost parameters (e.g.,opportunity cost, wages, risk, etc.) of a persona data structure in thepersonas datastore 512 and of a resource data structure in the resourcesdatastore 514, and updates the project workflow datastore 516 to includethe cost parameters. In a specific implementation, the cost parametersimpact not only a project that includes a relevant asset synthesisinstance, but also projects that are impacted by opportunity costs.

FIG. 6 depicts a diagram 600 of an example of a workflow analyticsengine. The diagram 600 includes an asset qualification engine 602, apersonas datastore 604 coupled to the asset qualification engine 602, aresources datastore 606 coupled to the asset qualification engine 602, aproject workflow datastore 608 coupled to the asset qualification engine602, a task completion prediction engine 610 coupled to the assetqualification engine 602, a task workflow datastore 612 coupled to thetask completion prediction engine 610, a project completion predictionengine 614 coupled to the task completion prediction engine 610, and aproject workflow datastore 616 coupled to the project completionprediction engine 614.

The asset qualification engine 602 is intended to represent an enginethat rates persona data structures in the personas datastore 604 andresource data structures in the resources datastore 606 using projectworkflow data structure parameters in the project workflow datastore608. In a specific implementation, human agents provide a rating forresources assigned to an asset synthesis instance, such as the impact ofthe resource on task completion, which is stored in association with theresource. Alternatively or in addition, asset (persona and resource)costs are combined to obtain overhead for an asset synthesis instanceand compared to an overhead threshold such as an organization meetingcost target, a control threshold (actually or theoretically computed todetermine cost for projects in which asset synthesis instances areomitted), or an ideal threshold (typically theoretically or predictivelycomputed to determine cost for projects in which a workflow isstrategically populated with asset synthesis instances), to name a few.

In a specific implementation, the asset qualification engine 602includes a strike rate computation engine (not shown). Strike rate isdefined as tasks completed per unit time of asset synthesis instances inwhich a human agent represented as a persona data structure in thepersonas datastore 604 is a participant. A 100 minute unit time has beenfound to be a convenient value in a hypothetical business workflow, butpreferences may vary. Because it is easy to manipulate numbers to removefractions, it makes little difference whether the strike rate is 1minute unit time or 100 hours unit time because the strike rate can bemultiplied by a value when presenting to a human agent (forreadability), but 100 minutes has been found to require no manipulationto aid readability in at least one white collar business context. It maybe desirable to use a logarithmic scale if strike rates vary a greatdeal between human agents, though it seems unlikely strike rate valueswill be so disparate as to require a logarithmic scale unless comparingdramatically different individuals.

The task completion prediction engine 610 is intended to represent anengine that uses a mean strike rate parameter of a persona datastructure in the personas datastore 604 and a complexity parameter of atask data structure in the task workflow datastore 612 to predict timeto complete a target task. Instead or in addition, the persona datastructure includes a behavior pattern for completing a task reckoned tobe similar to the target task, which the task completion predictionengine 610 uses to predict time to complete the target task.Extrapolating a persona's behavior pattern in completing a task that isreckoned to be similar to a target task to predict time to complete thetarget task by comparing similar characteristic data after large amountof data is accumulated in a business workflow datastore may improveprediction accuracy.

The project completion prediction engine 614 is intended to represent anengine that considers each component task of a project data structure inthe project workflow datastore 616 to predict a project completion time.Advantageously, the project completion prediction engine 614 can make arelatively straight-forward prediction because the task completion timeshave already been modified to take into account asset (human andresource) availability to conform to organizational targets, making theproject prediction essentially a sum of task completion predictionsminus time tasks that can be completed in parallel.

FIG. 7 depicts a diagram 700 of an example of a workflow-to-realityintegration engine. A workflow-to-reality integration engineincorporates the principle that at least three variables impact taskcompletion: resource availability, staff proficiency, and supervisorcapabilities. Resource availability may mean availability of a resourcewith a constraint (e.g., a cost constraint). Staff proficiency becomesincreasingly relevant as assignments become increasingly specialized.Supervisor capabilities can include maneuverability within a constraint(e.g., a cost constraint). The diagram 700 includes a supervisorinterface engine 702, a personas datastore 704 coupled to the supervisorinterface engine 702, a resources datastore 706 coupled to thesupervisor interface engine 702, a task workflow datastore 708 coupledto the supervisor interface engine 702, and an asset synthesis instanceimpact display engine 710 coupled to the supervisor interface engine702.

The supervisor interface engine 702 is intended to represent an enginethat enables a supervisor to access meaningful metrics regarding humanagents represented as persona data structures in the personas datastore704, qualified resources represented as resource data structures in theresources datastore 706, and tasks represented as task workflow datastructures in the task workflow datastore 708, the combination of whichrepresent a historical record of a real world implementation of the taskor a planned or predicted real world implementation of the task.

The asset synthesis instance impact display engine 710 is intended torepresent an engine that computes impact for provisioning to asupervisor via the supervisor interface engine 702. In a specificimplementation, impact level is computed as a sum of asset synthesisinstance times divided by the time taken to complete a task; taskcomplexity is easy, average, or complex (as set by a human agent, suchas a supervisor of the task, or an artificial agent), and impact rangeis categorized as 0-33% (low impact, high index), 33-66% (medium impact,medium index), and 66-100% (high impact, low index). A Complex Taskcompleted with fewer and shorter asset synthesis instances (e.g.,meetings and meeting times) is indicative of a good maneuveringcapability of a supervisor. In other words, direction given to staff ismore likely to be clear, meetings are more likely to have been conductedefficiently, etc. This would generally be considered a valuable qualityin a supervisor. On the other hand, an easy task completed with more andlonger asset synthesis instances is indicative of poor maneuveringcapability of a supervisor.

A matrix used for gamifying the task completion process is as follows:

TABLE 1 Method to find persona ratings based on task completioncapability. Low Impact Medium Impact High Impact Complex: Rating ARating D Rating G Average Complexity: Rating B Rating E Rating H Easy:Rating C Rating F Rating I

When number of tasks is less, the averaged out zone can be treated as arating of a persona. With more numbers, clusters are grouped and arating can be based on the average. In the 3×3 matrix of this example,there are 9 zones where a task completion rating of a persona couldfall. With sparse task completion data, data points are treatedindividually; the placement of an averaged data point falling in a zoneis treated as the rating of a persona. With denser task completion data,data points falling in close proximity are clustered; the placement ofaveraged cluster falling in a zone is treated as the rating of apersona. The alphanumeric rating (e.g., Rating A, Rating B, . . . ) isintended, in this example, to be representative of vertical sequencingof zones. In an alternative, the 3×3 matrix can be replaced with an N×Nmatrix because x-axis (impact scale) and y-axis (complexity scale) canbe subdivided depending upon implementation-specific,configuration-specific, preference-specific, or other factors. Inanother alternative, the zones are horizontally sequenced, which wouldhave the effect of “complex task, high impact meeting” having a betterrating than “easy task, low impact meeting.”

FIG. 8 is a flowchart 800 of an example of task completion. Forillustrative simplicity, asset synthesis instances are limited tomeetings and completion of a single task is presented. The flowchart 800starts at module 802 where a task is delegated to a supervisor. Taskdelegation can be accomplished via a workflow generation engine, such asthe workflow generation engine 116 (FIG. 1), or the task delegationengine 208 (FIG. 2). An officer or agent acting with officer-levelauthority can delegate one or more tasks from one or more projects, butfor simplicity, the delegation of a single task is illustrated in theexample of FIG. 8. Advantageously, an officer can take advantage ofknowledge of personas and resources and, in particular, task (orassignment) dependencies, allowing for delegations that optimize metrics(e.g., throughput, cost, or the like, potentially with activityprioritization) across assignments, tasks, and projects. Supervisoravailability may be impacted by the delegation of tasks such thatdelegating the task to the supervisor at module 802 can be impacted bydelegation of as-of-yet incomplete tasks or intended delegation totasks; this can be characterized as choosing an available supervisor forthe delegation. The choice of supervisor may also be impacted by arating, qualification, or other parameter of a persona data structureassociated with the supervisor; this can be characterized as choosing anappropriate supervisor for the delegation. For illustrative simplicity,there is no option in the example of FIG. 8 to re-assign a supervisor tothe task, but it may be noted re-delegation would likely be possible inmost implementations because supervisors can leave or be asked to leavefor a number of reasons and tasks must still be completed.

The flowchart 800 continues to module 804 where the supervisor (andlater staff to which assignments are delegated, if applicable) works toprogress the task. The supervisor (and/or staff) typically haveresources available to enable them to accomplish their tasks, such as acomputer, telephone, desk, or other office equipment; smartphone,glasses (to the extent perception enhancement is tracked), automobile,or other personal items, whether owned by the company or the individual;and software licenses, certifications, credit cards, or otherpermissions, qualifications, or access. Resources that are alwaysavailable (or are available because they are personally owned) may besufficient to work to progress a task. At times, however, it may becomenecessary to create an asset synthesis instance to bring together one ormore humans and scarce resources.

The flowchart 800 continues to decision point 806 where the supervisor(or an agent acting on authority thereof) determines whether to delegatean assignment. If it is determined assignments are to be delegated(806—Yes), then the flowchart 800 continues to module 808 where thesupervisor (or an agent acting on behalf of the supervisor) delegates anassignment to a staff member. The staff members may or may not bepre-associated with the relevant task workflow, e.g., at or beforemodule 802. Available and appropriate staff members can also beassociated with a task workflow, e.g., at module 804 (as part of workingto progress a task) or module 808 (by virtue of or as part of thedelegation of an assignment). Assignment delegation can be accomplishedvia a workflow generation engine, such as the workflow generation engine116 (FIG. 1) or the assignment delegation engine 212 (FIG. 2).

If it is determined assignments are not to be delegated (806—No) orafter assignments are delegated (808), the flowchart 800 continues todecision point 810 where the supervisor (or an agent acting on authoritythereof) determines whether to call a meeting. Determining a task forwhich asset synthesis instances (including, specifically for thisexample, meetings) are appropriate can be accomplished via an assetsynthesis instantiation engine, such as the asset synthesisinstantiation engine 122 (FIG. 1) or the task selection engine 402 (FIG.4). Advantageously, a supervisor can take advantage of knowledge ofpersonas and resources and, in particular, task (or assignment)dependencies, allowing for delegations that optimize metrics (e.g.,throughput, cost, or the like, potentially with activity prioritization)across assignments, tasks, and projects. For illustrative simplicity,asset synthesis instances in the example of FIG. 8 are limited to“meetings,” which are a subset of asset synthesis instances, which couldalso include conferences, appointments, performances, meals,entertainment, or the like. It may be noted asset synthesis instancescan be entered retroactively; for example, a chance meeting betweenstakeholders could be entered after the meeting already occurred.

If it is determined to call a meeting (810—Yes), then the flowchart 800continues to module 812 where a meeting agenda is prepared. In aspecific implementation, a meeting agenda is prepared by the supervisoror an agent operating with the authority of the supervisor and themeeting agenda is made a part of a task workflow. Asset synthesisinstances (including, specifically for this example, meetings) can beaccomplished via an asset synthesis instantiation engine, such as theasset synthesis instantiation engine 122 (FIG. 1), or the agendacreation engine 406 (FIG. 4).

The flowchart 800 continues to module 814 where staff are invited to themeeting. Population of asset synthesis instances (including,specifically for this example, meetings) can be accomplished via anasset synthesis instantiation engine, such as the asset synthesisinstantiation engine 122 (FIG. 1), or the stakeholder invitation engine410 (FIG. 4).

The flowchart 800 continues to module 816 where the supervisor (or anagent acting on authority thereof) prepares meeting minutes.Memorialization of asset synthesis instances (including, specificallyfor this example, meetings) can be accomplished via an asset synthesisinstantiation engine, such as the asset synthesis instantiation engine122 (FIG. 1), or the asset synthesis instance monitoring engine 418(FIG. 4). Memorialization of an asset synthesis instance can also beaccomplished after the asset synthesis instance is complete via an SPIoutcome generation engine, such as the SPI outcome generation engine 124(FIG. 1), or the workflow update engine 502 (FIG. 5).

The flowchart 800 continues to module 818 where time spent on themeeting is reported. In a specific implementation, the report isgenerated by an agent and sent to an analytics engine. Although in aspecific implementation the analytics engine has access to a variety ofmeeting-specific parameters (such as, e.g., cost), the time parametersare used in this example for illustrative simplicity. Providingparameters of an asset synthesis instance can be accomplished via an SPIoutcome generation engine, such as the SPI outcome generation engine 124(FIG. 1), or the workflow update engine 502 (FIG. 5). The analyticsengine can be implemented as an SPI outcome generation engine, such asthe SPI outcome generation engine 124 (FIG. 1), or the asset synthesisinstance cost computation engine 510 (FIG. 5). Alternatively, theanalytics engine can be implemented as a workflow analytics engine, suchas the workflow analytics engine 126 (FIG. 1).

The flowchart 800 also returns to decision point 806 and continues asdescribed previously. Precisely when the flowchart 800 returns todecision point 806 depends upon configuration-specific,preference-specific, or other considerations. For example, thesupervisor may decide to delegate while preparing a meeting agenda(812), while staff are being invited (814), while meeting minutes arebeing prepared (816), while time spent on the meeting is being reported(818), or before or after any of the modules 812, 814, 816, 818.

It may be noted that delegation of assignment (808) can occur during ameeting, in which case the module 808 could be considered part of ameeting super-module 820 in those instances in which delegation is partof the meeting. As illustrated in the example of FIG. 8, the modules812, 814, 816, and 818 are also part of the meeting super-module. Otherconceptual groupings are the modules 812, 814 as a “meeting creation”super-module or the modules 816, 808 (when applicable) as a “duringmeeting” super-module. To the extent the module 804 includes a taskselection process preceding a meeting, the module 804 (when applicable)could also be considered part of the “meeting creation” super-module.

Returning once again to decision point 810, if it is determined not tocall a meeting (810—No), then the flowchart 800 continues to decisionpoint 822, where it is determined whether the task is complete. If it isdetermined the task is not complete (822—No), then the flowchart 800returns to module 804 and continues as described previously. If, on theother hand, it is determined the task is complete (822—Yes), then theflowchart 800 continues to module 824 where time spent on the task isreported. Advantageously, reporting the time spent to complete a task(in combination with analytics) enables a more accurate estimate of howlong it takes to complete future tasks both at the outset and at anystage, which reduces the common task management problem of determininghow much of a task has actually been completed (which can be analyzed onany applicable metric, such as cost, though a time metric is typical).In a specific implementation, the report is generated by an agent andsent to an analytics engine. A supervisor (or an agent acting on thesupervisor's behalf) can indicate the task is complete via aworkflow-to-reality integration engine, such as the workflow-to-realityintegration engine 130, which sends the report.

The flowchart 800 ends at module 826 where the analytics moduleestimates meeting impact on the task. Advantageously, the contributionof meetings to task completion can be made readily available to projectand task management tools of an organization to improve productivity.The analytics engine can be implemented as a workflow analytics engine,such as the workflow analytics engine 126 (FIG. 1), or the assetqualification engine 602 (FIG. 6). The start and end of the flowchart800 is intended only for conceptual purposes, a task can be initiatedbefore it is assigned to a supervisor (802) and the impact of the taskcan extend beyond the meeting impact estimate (826).

FIG. 9 is a flowchart of an example of changing task priority. Theflowchart 900 starts at module 902 where an officer delegates to asupervisor a task having a first complexity and a first priority. Theflowchart 900 continues to module 904 where a supervisor delegates tostaff an assignment having the first priority. The flowchart 900continues to decision point 906 where it is determined whether the taskis to be given a second priority. If not (906—No), the flowchart 900ends. If so (906—Yes), the flowchart 900 continues to module 908 wherethe assignment is given a second priority, to module 910 where personaand resource availability parameters are updated, and then the flowchart900 continues to decision point 906, as described previously.

Reference is now made to a series of screenshots to illustrate animplementation in use. John is a CEO of a company; John has projects asgoals. Francis is a product manager within the company; Francis can becharacterized as having projects or tasks as goals. Paul is an associatewith experience coordinating with domain experts, such as engineers andmarketers; Paul can be characterized as having tasks as goals. John candelegate a project to an officer, such as Francis. Francis can delegatetasks to a supervisor, such as Paul. Paul can delegate assignments tostaff.

FIG. 10 is a screenshot 1000 of Paul on a Work Delegator tab of a WorkManager page. The screenshot 1000 illustrates three assignments (1.Raising the bar, 2. World of changes, and 3. Setting the XYZ), delegatedstaff (@Bidroos, @Sudindra, and @Ravindra), complexity (CT and ET), andduration (75 days and 5 days). In this example, the third assignmentdoes not have an associated complexity (neither ET, or Easy Task, MT, orModerate Task, nor CT, or Complex Task; other complexities are alsopossible, such as ST, or Simple Task) or duration. In this example, the@ symbol is typed prior to a name to indicate delegation and actionpoints can be added later to previously delegated work as one optionwhen selecting the + symbol next to a designee, though in this example,the + symbol was selected to add complexity and duration.

It is assumed in this example a moderate task has been allotted to asupervisor, Paul, and Paul wants to convert the moderate task to acomplex task. FIG. 11 is a screenshot 1100 of Paul on a Your Tasks tabof the Work Manager page. The screenshot 1100 illustrates three tasks(all have the same name) with associated Complexity (MT, CT, LT),Duration (98 days, 100 days, 60 days), Initiator (Manager, Manager,Marketer), Initiation Approval (Done, Done, Send Reminder), and TaskStatus (Pending, Happening, Pending). Note: The pending tasks statusesalso have an indication of lag (Lag by 12 days, Lag by 25 days). FIG. 12is a screenshot 1200 of Paul on the Your Tasks tab of the Work Managerpage. The difference between the screenshot 1100 and the screenshot 1200is that the complexity drop-down menu has been selected in thescreenshot 1200, enabling the selection of MT, CT, or ST. FIG. 13 is ascreenshot 1300 of a pop-up window that followed the selection of the CTcomplexity illustrated in screenshot 1200. It is assumed Paul selectsYes in the answer to the query in the popup window. (“Are you sure thatyou want to convert this into a Complex Task?”)

FIG. 14 is a screenshot 1400 of Paul on the Your Tasks tab of the WorkManager page. The screenshot 1400 illustrates three tasks, much like inscreenshot 1100, but the complexity of the first project has beenchanged to CT and underneath the complexity of the first project is thetext “pending change approval.”

Following the screenshot 1400, it is assumed Paul's manager, Francis,opens his Work Manager application. FIG. 15 is a screenshot 1500 ofFrancis on the Today's tab of the Your Meetings page. Francis has 2 HRSLEFT to respond with “Will be late” or “Cannot attend.” The onlinemeeting is for from 2:30-3:30 PM EST for Project 125. A summary of themeeting agenda is 1. Getting the Technical team onboard 2. Working onthe debut 3. Making things new 4. Renew the feature and work on the oldone 5. Making fresh start to meetings on the leverage. Francis canselect from the hypertext links: Add my materials, View details, Sendsomeone instead, or Add more people. FIG. 16 is a screenshot 1600 ofFrancis on a Task Approver tab of a Work Manager page. The screenshot1600 illustrates Paul wants to convert this action (identified below) tocomplex task and the time and date of the request (11:30 am 25 Aug.2017). Francis has the option to Approve or Decline. FIG. 17 is ascreenshot 1700 of Francis on the Task Approver tab of the Work Managerpage. The difference between the screenshot 1600 and the screenshot 1700is that Francis has approved the change of task complexity as indicatedby the “Approved!” text where the Approve button used to be.

The approval is represented on Paul's Work Manager page, as illustratedin screenshot 1800 of FIG. 18, which is similar to the screenshot 1400(FIG. 14) except the complexity of the first project is no longerpending change approval.

Refer once again to the screenshot 1100 (FIG. 11), but instead ofchanging complexity, Paul will now change Task Status. FIG. 19 is ascreenshot 1900 of Paul on the Your Tasks tab of the Work Manager page.The screenshot 1900 illustrates Paul has selected the task statusdropdown menu, which has the options Pending (unchanged) and Completed.FIG. 20 is a screenshot 2000 of a pop-up window that followed theselection of the completed status illustrated in the screenshot 1900. Itis assumed Paul selects Yes in the answer to the query in the popupwindow. (“Are you sure that you have completed this task?”) FIG. 21 is ascreenshot 2100 of Paul on the Your Tasks tab of the Work Manager page.The screenshot 2100 illustrates three tasks, much like in screenshot1100, but the status of the first task has been changed to completed andunderneath the task status of the first project is the text “pendingchange approval.”

Following the screenshot 2100, it is assumed Paul's manager, Francis,opens his Work Manager application. FIG. 22 is a screenshot 2200 ofFrancis on a Your Team's Tasks tab of a Work Manager page. Thescreenshot 2200 illustrates Paul has completed the following task(identified below) and the time and date of the status change (11:30 am25 Aug. 2017). Francis has the option to Approve or Decline. FIG. 23 isa screenshot 2300 of Francis on the Your Team's Tasks tab of the WorkManager page. The difference between the screenshot 2300 and thescreenshot 2200 is that Francis has approved the status change asindicated by the “Approved!” text where the Approve button used to be.

The approval is represented on Paul's Work Manager page, as illustratedin screenshot 2400 of FIG. 24, which is similar to the screenshot 2100(FIG. 21) except the status of the first project is no longer pendingchange approval, so the task has been omitted (leaving only two tasks).FIG. 25 is a screenshot 2500 of Paul's Work Manager page illustratingPaul can select the “Completed” subtab under “Your Tasks” to view thenow-completed task.

FIG. 26 is a screenshot 2600 of Francis on the Your Team's Tasks tab ofa Work Manager page. Francis can choose a member from a drop-down menu,which is currently selected to show the choices of Paul, ABC, and CBC.After selecting Paul, Francis has the option to view ON-GOING,COMPLETED, and CANCELLED tasks delegated to Paul. FIG. 27 is ascreenshot 2700 of Francis on the Your Team's Tasks tab of a WorkManager page after choosing Paul, with the ON-GOING member-specific tabchosen, which causes Paul's on-going tasks to be listed much as Paulcould view them (see, e.g., FIG. 24). Francis also has the option ofchoosing a new project for Paul by selecting a “Create new task forPaul” button. FIG. 28 is a screenshot 2800 illustrating what follows, inthis example, when a new task is delegated. Specifically, for theproject summary “create a new methodology for sequences” Francis canselect complexity (MT in the screenshot 2800), duration (85 in thescreenshot 2800), project (112 in the screenshot 2800), and an “Assignnow” button to delegate the task with the indicated parameters.Advantageously, the delegation can be accomplished without calling for ameeting.

FIG. 29 is a screenshot 2900 of Paul on a Your Tasks tab of a WorkManager page. The screenshot 2900 is similar to the screenshot 2400, butPaul opens his Work Manager and finds the new task assigned with taskstatus “Happening,” along with the two tasks illustrated in screenshot2400.

Francis sets the priority to a task of Paul's. All associated tasks ofhis team members have correspondingly changed priority status, which isreflected on their pages. Refer once again to the screenshots 2600, 2700(FIGS. 26, 27), but instead of creating a new task for Paul, Franciswill change task priority. FIG. 30 is a screenshot 3000 of Francis on aYour Team's Tasks tab of a Work Manager page after selecting Paul'son-going tasks. As illustrated in a pull-down menu, Francis can chooseto Set top Priority, Add new action to the task, Assign this to adifferent person, Convert an action in other task, or Cancel this task.FIG. 31 is a screenshot 3100 similar to the screenshot 2700, but with anicon that is intended to indicate priority has been changed for a task.

Paul can see the priority task highlighted after selecting a Your Taskstab on a Work Manager page, as is illustrated in FIG. 32, screenshot3200, which includes a HIGH PRIORITY TASKS section identifying a highpriority task (in this example, “Sessions Analytics feature”).Similarly, for each applicable teammate of Paul, assignments of theapplicable task will be shown as corresponding pending high priorityassignments for the teammates. It may be noted that the link can be fortasks or assignments, and in practice the terms are sometimes usedsynonymously, but “assignments” are used for the purpose of this examplebecause they are the components of the larger task. (Of course, taskscan have sub-tasks and even tasks on the same hierarchical level canhave associations that put one task “under” another task for practicalpurposes.) Link establishment is generated by assignments associatedwith a task obtained through delegation, either explicitly (through asupervisor) or implicitly (through an artificial agent). It may be notedthat in some implementations, unlinked tasks will not appear in apriority suggestion list. One solution to this problem is to ensure taskcreation or delegation occurs during asset synthesis instances.

For illustrative purposes, assume Paul completes a meeting during whichassignments for the task “Session Analytics Feature” are delegated toRahul and Hang Si. FIG. 33 is a screenshot 3300 of a session detailsummary for an asset synthesis instance (a meeting in this example),which includes a duration, an option to play meeting video, where themeeting took place (Hall No B 112 in this example), the organizer(Paul), attendees (Rahul and Hang Si), assignment delegations (“GettingUI ready for session analytics” delegated to Rahul, MT, 55 days; and“Development work for session analytics” delegated to Hang Si, MT, 90days), and some other details, such as Questions, Polls, and Highlights.

FIG. 34 is a screenshot 3400 of Rahul on a Your Tasks tab of a WorkManager page that includes “Getting UI Ready for session analytics” in aHigh Priority Tasks section (and, in this example, listed redundantly,but in more detail, in an on-going tasks section). Advantageously, thepriority of the assignment is inherited from the priority of the parenttask.

We will now consider a scenario in which work movement is from bottom totop. Assume Paul encountered an obstacle on his journey to complete atask, so he lets Francis know the seriousness of the issue by schedulinga meeting. Francis asks Paul to delegate the task upward to Francis suchthat, when Francis opens his Work Manager application, he finds the taskin his “Your Tasks” section. FIG. 35 is a screenshot 3500 of Paul on aScheduled Meetings tab on which Paul can choose meeting preferences(e.g., “Face to Face” as opposed to, e.g., “Online”), “With your bosses”(as opposed to, e.g., “With your team and stakeholders”), and “Task” (asopposed to, e.g., “Milestone” or “Interaction”). FIG. 36 is a screenshot3600 of Paul on the Scheduled Meetings tab on which Paul can prepare anagenda and pick stakeholders (task, e.g., “Engineering of Action controlfeature;” agenda summary, e.g., “1. Couldn't continue because of serverissue; 2. Audio Video option related issues;” stakeholders, e.g., Paul,the organizer, and Francis; and materials). FIG. 37 is a screenshot 3700of Paul on the Scheduled Meetings tab on which Paul can schedule ameeting at the appropriate time, including date, approximate duration,invitation mail, suggested time (including, e.g., “pick your own”), andsuggested location (including, e.g., “pick your own”).

FIG. 38 is a screenshot 3800 of Francis in a Your Meetings tab fortoday's meetings, in which the meeting Paul scheduled is indicated.Francis can choose to join at the indicated location or remotely and canalso indicate if he will be late or cannot attend, add materials, viewdetails, send someone else instead, or add more people. (Paul can beassumed to have a similar page for today's meetings.) The agenda can bediscussed, with items listed out as illustrated in FIG. 39, which is ascreenshot 3900 of a MoM Creator portion of Session Details, includingDuration (25:30 mins in this example). In the example, items of theagenda have associated checkboxes and two of the checkboxes are checkedto indicate Francis has had work delegated to him. FIG. 40 is ascreenshot 4000 of a Summary portion of Session Details, which includesan option to Play Meeting Video, identifies location and attendees,includes the delegated items, and includes a section for questions,polls, and highlights. FIG. 41 is a screenshot 4100 of Francis in a WorkDelegator tab of a Work Manager, which includes tasks delegated during(or following) the meeting, which can be added as action points to tasksor ignored. Paul can create a new meeting for the same task, asillustrated in FIG. 42, which is a screenshot of Paul on the ScheduledMeetings tab on which Paul can prepare an agenda and pick stakeholders,much like was illustrated in FIG. 36, but with a suggested agenda andstakeholders, along with the option to dig deeper into the suggestedagenda. Of course, any information about tasks of a project orassignments of a task can be provided as suggestions, even if no meetinghas been held.

1. A method comprising: virtually synchronizing a first persona of aplurality of personas in a persona datastore and a second persona of theplurality of personas in the persona datastore; matching a resource of aplurality of resources in a resource datastore to the first persona andthe second persona to generate an asset synthesis instance;instantiating an asset synthesis instance in an event occurring in thephysical world that includes the first persona, the second persona, andthe resource.
 2. The method of claim 1, wherein the asset synthesisinstance is generated to optimize one or more of cost, speed, andthroughput.
 3. The method of claim 1, wherein the resource is selectedfrom the group consisting of a device, a camera, a network, a display, asoftware license, a wireless access point (WAP), a conference room,furniture, local catering, hotel accommodations, and a combination ofthese.
 4. The method of claim 1, wherein the first persona and thesecond persona have respective designations of a role selected from thegroup consisting of director, officer, supervisor, staff, outsidepersona, and a combination of these.
 5. The method of claim 1,comprising: generating a business workflow; integrating the assetsynthesis instance, including the first persona, the second persona, andthe resource, into the business workflow; updating the business workflowin real time during the event using input from human or artificialagents.
 6. The method of claim 1, comprising using a sensor to updatethe asset synthesis instance in real time during the event occurring inthe physical world, wherein the sensor is selected from the groupconsisting of a radio frequency identification (RFID) sensor, a camera,a microphone, a plurality of these, and a combination of these.
 7. Themethod of claim 1, comprising generating information about the firstpersona, the second persona, and the resource to assist in theperformance of a task selected from the group consisting of assessperformance, predict progress and results across one or more workflows,generate information for use in modeling future workflows, and acombination of these.
 8. The method of claim 1, comprising generating areport regarding the event.
 9. The method of claim 1, comprisingproviding an interface to one or more human agents regardingeffectiveness of the asset synthesis instance in the physical world. 10.A system comprising: a workflow generation engine configured to generatea business workflow using personas in a persona datastore and resourcesin a resource datastore; a persona-to-persona connectivity engineconfigured to connect a first persona of the personas and a secondpersona of the personas; a synchronized persona interaction (SPI)facilitation engine configured to synchronize the two or more personasvirtually; an asset synthesis instantiation engine configured to match aresource of the resources to the first persona and the second persona togenerate an asset synthesis instance; a workflow-to-reality integrationengine configured to integrate the asset synthesis instance into thebusiness workflow; an asset synthesis instantiation engine configured toinstantiate the asset synthesis instance in an event occurring in thephysical world.
 11. The system of claim 10, wherein the asset synthesisinstance is generated to optimize one or more of cost, speed andthroughput.
 12. The system of claim 10, wherein the resource is selectedfrom the group consisting of a device, a camera, a network, a display, asoftware license, a wireless access point (WAP), a conference room,furniture, local catering, hotel accommodations, and a combination ofthese.
 13. The system of claim 10, wherein the first persona and thesecond persona have respective designations of a role selected from thegroup consisting of director, officer, supervisor, staff, outsidepersona, and a combination of these.
 14. The system of claim 10,comprising an SPI outcome generation engine configured to update thebusiness workflow in real time during the event using input from humanor artificial agents.
 15. The system of claim 10, comprising a sensor toupdate the business workflow in real time during the event occurring inthe physical world, wherein the sensor is selected from the groupconsisting of a radio frequency identification (RFID) sensor, a camera,a microphone, a plurality of these, and a combination of these.
 16. Thesystem of claim 10, comprising a workflow analytics engine configured togenerate information about the first persona, the second persona, andthe resource to assist in performance of a task selected from the groupconsisting of assess performance, predict progress and results acrossone or more workflows, generate information for use in modeling futureworkflows, and a combination of these.
 17. The system of claim 10,comprising an SPI outcome generation engine configured to generate areport regarding the event.
 18. The system of claim 10, comprising aworkflow-to-reality integration engine configured to provide aninterface to one or more human agents regarding effectiveness of theasset synthesis instance in the physical world.
 19. The system of claim10, wherein the workflow generation engine is configured to provide aprediction with a probability that the business workflow will go asplanned.
 20. A system comprising: a means for virtually synchronizing afirst persona of a plurality of personas in a persona datastore and asecond persona of the plurality of personas in the persona datastore; ameans for matching a resource of a plurality of resources in a resourcedatastore to the first persona and the second persona to generate anasset synthesis instance; a means for instantiating an asset synthesisinstance in an event occurring in the physical world that includes thefirst persona, the second persona, and the resource.